Conventionally, data perspectives are static and limited to a cube data structure or object. However, such conventional data perspective analysis tools are limited to a subset of the features of a cube. In such conventional cube data structures, perspectives do not include data elements that are not defined in the parent cube, or data elements that are outside the parent cube object. Such conventional perspective analysis tools are limited to specific software and hardware platforms. In large organizations, where multiple data objects reside on multiple different types of databases, each having their own data structures, such limitation of restricting perspectives to being within the cube data structure or subsets thereof is detrimental to full utilization of business intelligence and analytics. Further, conventional data perspectives have a limited definition of being a subset of a model, implying static predetermined data arrays.
In view of the foregoing, conventional data perspective systems and methods have certain limitations and problems, e.g., being static and limited in perspective analysis capabilities.